Special issue information
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Journal:
Library Trends
Title:
Learning analytics and the academic library: Critical questions about real and possible futures
Guest editor:
Kyle M. L. Jones
Abstract submission deadline:
April 1, 2018
Publication date:
March, 2019
For more information, see https://www.press.jhu.edu/
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Nature and scope of this issue
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Learning analytics is the “measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.”[1] If the academic library is the “most important observation post” for understanding how students learn, then it follows that libraries in colleges and universities should be a primary focus of data mining and analysis initiatives in higher education.[2] Integration of library data in learning analytics is fledgling at best, but there are growing calls for such activity to increase, especially to enhance a library’s ability to prove their resource expenditures and demonstrate alignment with wider institutional goals (e.g., improve learning outcomes, decrease costs, etc.).[3]
The efficacy of learning analytics is premised on an institution’s ability to identify, aggregate, and manage a wide variety and increasingly large volume of data about students, much of which needs to be identifiable in order to develop personalized, just-in-time learning interventions. So, in the fashion of other Big Data initiatives, institutions are beginning to dredge their information systems for student behaviors, personal information, and communications, all of which hold potential to reveal how students learn and uncover structural impediments to learning.
It is enticing to assume good things about library participation in learning analytics. The profession wants to provide just the right information at just the right time, and professional librarians want that information to aid students as they develop personally, academically, and professionally. Moreover, the profession seeks to further cement its position as a key player in the educational experience, and learning analytics may enable librarians to make stronger claims about their pivotal role once they gain access to new sources of data and the metrics that come from data analysis. But, like all technologies, learning analytics are not neutral; they are embedded with and driven by political agendas, which may not be congruent with—or necessarily aware of—extant values and ethical positions, such as those espoused by academic librarians and users of their libraries.[4] Consequentially, scholars and practitioners need to take a critical approach to the growing role of learning analytics in academic libraries and the wider higher education context in order to better inform conversations concerning the intended and unintended positive and negative outcomes learning analytics can bring about.
This special issue is motivated by Neil Selwyn’s position that the “purposeful pursuit of pessimism” as it relates to educational technologies is constructive and fruitful.[5] In contrast, optimism around emerging technologies—and the denial of critical voices—perpetuates a belief that technological progress is always a good thing. While we often perceive a pessimistic attitude towards technology as destructive or equate it to traditional Luddism, there is actually much to be gained by critically questioning the political agendas driving educational technology design, adoption, and diffusion.
This issue will invite authors to explore and push back against statements that learning analytics will somehow improve academic libraries by addressing questions around political positions and value conflicts inherent to learning analytics, coded in related information systems, and embedded in emerging data infrastructures.
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Instructions for submission
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The guest editor requests interested parties to submit an abstract of 500 words or less, following Chicago format for parenthetical and reference list citations, by April 1, 2018. Abstracts should be sent to kmlj@iupui.edu with the subject of “Library Trends: Abstract Submission.”
For more information, see https://www.press.jhu.edu/
[1] Siemens, G. (2012). Learning analytics: Envisioning a research discipline and a domain of practice. Proceedings of the Second International Conference on Learning Analytics and Knowledge, USA, 4–8. doi: 10.1145/2330601.2330605
[2] Duderstadt, J. J. (2009). Possible futures for the research library in the 21st century. Journal of
Library Administration, 49(3), 217–225. doi: 10.1080/01930820902784770
[3] Connaway, L. S., Harvey, W., Kitzie, V., & Mikitish, S. (2017). Academic library impact: Improving practice and essential areas to research (Report). Retrieved from Association of College and Research Libraries website: http://www.ala.org/
[4] Jones, K. M. L., & Salo, D. (forthcoming – 2018). Learning analytics and the academic library: Professional ethics commitments at a crossroads. College & Research Libraries. Available as a preprint at http://crl.acrl.org/index.
[5] Selwyn, N. (2014). Distrusting educational technology: Critical questions for changing times. New York, NY: Routledge.
